I have an array
a = [1 2 3 4 5 6 7 8]
I want to get every group of 4
so the result is as such
[1 2 3 4]
[5 6 7 8]
I do not know how many elements there will be but I know it is divisible by 4
so something like a(1:4) and a(5:8) wont work, I can use a loop, but is there a way to not use a loop?
For an unknown number of elements in a you can use reshape you just need to figure out how many rows you will have in the final matrix or (better for your case) the number of columns.
a = 1:4*10;
a2 = reshape(a, 4, []).';
If you went the rows routine you would do this.
a = 1:4*10;
a2 = reshape(a, [], numel(a) / 4).';
You just need to be sure that a has the proper number of elements. numel simply tells you the total element count.
Related
I have a large array, which looks like this:
1
4
5
3
6
2
7
4
3
I want to rearrange this array that it looks like this:
7 4 3
3 6 2
1 4 5
My original array has the size 13700x1, so I cannot do it manually and if I use the reshape function, the array gets shaped in the wrong way:
1 3 7
4 6 4
5 2 3
I hope my intention is clear. Thanks!
Try
tmpArray = [1
4
5
3
6
2
7
4
3]
flipud(reshape(tmpArray, 3, 3).')
x = [1,4,5,3,6,2,7,4,3]';
A = flipud(reshape(x,3,3)');
The other answers assume your vector contains a square number of elements, 4, 9, 16 .... This is true for the example vector, but not for the one you're actually working with (it's 13700x1 according to the question).
This means that the flipud(reshape()) approach will give an error:
Product of known dimensions, 3, not divisible into total number of
elements, 13924.
This is not a problem if you don't want a square matrix, as numbers that can be represented as a product of any of the numbers: 2, 5, 137.
If you want a square matrix, you need to pad the vector with zeros, NaNs or something else. This can be done the following way:
A = randi(100,13700,1); %% Random 13700x1 matrix
n = numel(A); %% Number of elements in A (13700 in this case)
elements = ceil(sqrt(n))^2; %% Number of elements needed in order to make a square matrix
B = [A; zeros(elements-n,1)]; %% Pad the vectors with zeros.
%% You can also d0 B = [A; nan(elements-n,1)];
final_matrix = flipud(reshape(B, sqrt(elements),[]).'); %% Final operation
Given A = [3 4 5 6 7 8 9 10 11 1 2 3 4 5 6 8]
Output B = [3 4 5 6 8]
Is there a Matlab function or command to get this result? I am new to Matlab. Just now I am doing it going through for each element and keeping a counter for it. I have very big array so this is taking too much time.
Use a combination of unique and histc:
uA = unique(A); %// find unique values
B = uA(histc(A, uA)>=2); %// select those that appear at least twice
The above code gives the values that appear at least twice. If you want values that appear exactly twice, replace >= by ==.
I'm using Matlab, and I'm trying to come up with a vectorized solution for comparing the elements of one array to every element of another array. Specifically I want to find the difference and see if this difference is below a certain threshold.
Ex: a = [1 5 10 15] and b=[12 13 14 15], threshold = 6
so the elements in a that would satisfy the threshold would be 10 and 15 since each value comes within 6 of any of the values in b while 1 and 5 do not. Currently I have a for loop going through the elements of a and subtracting an equivalently sized matrix from b (for 5 it would be a = [5 5 5 5]). This obviously takes a long time so I'm trying to find a vectorized solution. Additionally, the current format I have my data in is actually cells where each cell element has size [1 2], and I have been using the cellfun function to perform my subtraction. I'm not sure if this complicates the solution of each [1 2] block with the [1 2] block of the second cell. A vectorized solution response is fine, there is no need to do the threshold analysis. I just added it in for a little more background.
Thanks in advance,
Manwei Chan
Use bsxfun:
>> ind = any(abs(bsxfun(#minus,a(:).',b(:)))<threshold)
ind =
0 0 1 1
>> a(ind)
ans =
10 15
I have around 100 1D arrays I'd like to merge to a matrix.
The arrays have 140 to 180 columns.
Is it possible to merge these 1 x (140-180) arrays to a matrix with a dimension of 100 (amount of arrays) x 180 ?
All the arrays contain numbers. I want to expand the 1x140 array to a 1x180 array by means of interpolation.
In a simplified form, it should be something like this:
A = [1 5 7 8 3]
B = [1 3 5]
result=
[1 5 7 8 3
1 2 3 4 5]
The array B (1x3) is expanded to an 1x5 matrix. And the values in between are interpolated.
Basically, I thought of using "vertcat" after all arrays are expanded by a same amount of columns.
Thanks in advance,
Koen
How about this?
array = {[1 5 7 8 3],[1 3 5]}; % example data
N = 5; % desired length (180 in your case)
aux = cellfun(#(v) interp1(linspace(0,1,length(v)),v,linspace(0,1,N)), array, 'uni', false);
result = cat(1,aux{:});
It uses linear interpolation. For your example, this gives
>> result
result =
1 5 7 8 3
1 2 3 4 5
Note that linear interpolation modifies all values of the vector except first and last, in general. For example, with N=5 the vector [1 3 4 5] would get interpolated to [1 2.5 3.5 4.25 5]. You could use other forms of interpolation by passing an extra argument to interp1, see help interp1.
suppose there are arrays A and B, both of which can have any arbitrary numbers and size. for example
A=[1 2 3]
B=[4 8 52 7 10]
i was wondering if there was any way to check if any of the elements in A are contained in B without using a loop? Once again, the numbers and size of the array will be arbitrary so i can't hard code it. Any help and input would be appreciated. Thanks!
You mean like this:
A=[1 2 3]; B=[4 8 52 7 10]
ismember(A,B)
ans =
0 0 0
Add to #NasserM.Abbasi: ismember will work regardless shapes and sizes, it is always element-wise. So if you have A=[1 2; 3 4] and B=[1 3; 4 2; 1 2],
then ismember will return :
ismember(A,B); % -> [1 1; 1 1] due to element-wise membership check
ismember(A,B, 'rows'); % -> [1 0] since it checks row-wise.
use ismember carefully according to the possible shapes in A and B.